MedicalResearch.com Interview with: Gaurav Pandey, Ph.D. Assistant Professor Department of Genetics and Genomic Sciences Icahn Institute of Data Science and Genomic Technology Icahn School of Medicine at Mount Sinai, New York  MedicalResearch.com: What is the background for this study?  Response: Multiparametric magnetic resonance imaging (mpMRI) has become increasingly important for the clinical assessment of prostate cancer (PCa), most routinely through PI-RADS v2, but its interpretation is generally variable due to its relatively subjective nature. Radiomics, a methodology that can analyze a large number of features of images that are difficult to study solely by visual assessment, combined with machine learning methods have shown potential for improving the accuracy and objectivity of mpMRI-based prostate cancer assessment. However, previous studies in this direction are generally limited to a small number of classification methods, evaluation using the AUC score only, and a non-rigorous assessment of all possible combinations of radiomics and machine learning methods. (more…)